Industry guide: Automotive
This guide highlights sessions and learning opportunities at re:Invent 2024 specifically for automotive professionals looking to learn more about automotive challenges, vehicle-to-cloud connectivity, autonomous driving development, and much more, all from AWS subject matter experts.
Ozgur Tohumcu
General Manager, Automotive and Manufacturing, AWS
Our mission at AWS is to help the automotive industry navigate the digital transformation journey into the software-defined vehicle era, utilizing the power of the cloud to build the future faster, together.
This guide outlines the sessions that feature content that is specific to automotive challenges, showcasing purpose-built services and solutions that help accelerate innovation in vehicle software development, vehicle-to-cloud connectivity, autonomous driving development, and digital customer experience enrichment.
Whether you’re interested in a breakout session, chalk talk, builders’ session, or workshop, there’s something for everyone at re:Invent to help you along your transformation journey. I hope you have an insightful, engaging, and fun week at re:Invent 2024. In the meantime, keep an eye on the AWS automotive blog and follow us on our LinkedIn page to stay up to date on all things automotive at re:Invent.
Breakout session
NET217-NEW | [NEW LAUNCH] Accelerate data transfer to the cloud with AWS Data Transfer Terminal
Transferring large datasets to the cloud poses challenges and can result in prolonged timelines and compromised data quality. This issue is relevant for use cases that generate large datasets, such as advanced driver assistance systems (ADAS), high-resolution video production, and industrial sensory monitoring data. Explore the secure, upload-ready physical locations of AWS Data Transfer Terminal, where you can connect your storage devices to the AWS backbone and initiate uploads to various AWS endpoints including Amazon S3 and Amazon EFS at speeds up to 400 Gbps. Get data into AWS quicker and improve time to market.
IOT202 | AWS IoT for edge LLM deployment and execution
With the advent of generative AI and large language models (LLMs), you must be wondering, how can these technologies be applied at the IoT edge? After all, there are many benefits of running LLMs at the edge—from network bandwidth efficiencies, offline processing, lower latency, and data sovereignty to cost savings, security, and differentiation. In this session, learn how using AWS IoT services and LLMs at the edge can uplift your solutions with actionable outcomes and innovative capabilities, such as gesture recognition, natural language processing for voice control, real-time predictive maintenance, energy optimization, anomaly detection, and more.
IOT205 | Beyond connectivity: Transforming businesses with intelligent IoT
This session explores how recent advancements in AI are evolving the Internet of Things (IoT) into an engine for real-world intelligence, autonomy, and actionable insights. Explore how an increasingly connected world is driving deeper systems-level intelligence across healthcare, consumer products, automotive, manufacturing, energy, and utilities. The HP Inc. team shares their journey revolutionizing the world of industrial printing through intelligent automation. Finally, learn how to get started with IoT and AI/ML services on AWS and patterns to accelerate time to value when building and deploying intelligent IoT products and solutions.
PRO201 | BMW speeds car development with a new app for defect ticket routing
The development and production of cars progressively becomes more software driven as the number of sensors and other digital components increases. BMW faces the challenge of routing and resolving tickets during the testing and development phases of designing a new car platform. With over 140 software teams across many areas, BMW now leverages a generative AI large language model (LLM) that provides recommendations on the next best action, augmenting the previously manual process and considering more data for correct team routing. This innovative solution streamlines BMW's software-driven car development process.
CMP204 | High performance computing: Reinvented to help you think truly big
As more customers bring their high performance computing (HPC) workloads to AWS, we’re engineering new solutions to make sure running at cloud scale is a success factor for those customers, not a challenge. In this session, experts walk you straight past some of the undifferentiated heavy lifting you no longer need to do to spin up thousands (or millions) of cores to solve a hard problem. In collaboration with a guest customer, learn what HPC looks like when it’s reinvented like this and how much easier it is to think really, truly big.
AUT202 | Honda’s EV charging experience with Amazon Bedrock and AWS IoT Core
Join this session to learn how Honda worked with AWS to redefine the in-vehicle EV charging experience. By combining data from its connected vehicle platform, external data sources, and layering in generative AI, Honda delivers a personalized, connected, and intelligent charging solution that caters to the evolving needs of EV owners. At the core of this experience is Honda’s use of Amazon Bedrock, providing drivers with personalized charging recommendations and route guidance by factoring in battery health data, driving patterns, and available charging stations.
AUT311 | How Ford unlocked real-time insights using Apache Iceberg on AWS
In the era of connected vehicles, it’s crucial for automakers to use real-time, data-driven insights to enhance customer experiences and drive operational efficiencies. This session explores Ford’s collaboration with AWS to develop the Event Store, a key component of Ford’s Transportation Mobility Cloud (TMC). This platform processes 4 TB of real-time data daily from over 20 million vehicles, allowing insights around OTA updates, vehicle command and control, and telemetry. Ford’s strategic adoption of AWS services facilitated a petabyte-scale data lake using Apache Iceberg, improving data management and analysis and reducing SLAs by 50% while meeting low-latency requirements.
PRO202 | Iveco Group and AWS: A story of continuous innovation
The session showcases how Iveco Group builds on AWS to drive innovation, collaboration, and digital transformation in virtual engineering, knowledge management, and generative AI-powered automation. Learn how Iveco is building a self-service development platform on AWS to enable faster development cycles and reduce hardware dependencies. The company’s Virtual Engineering Workbench fosters collaboration among developers, testers, and integrators by providing virtualized environments for digital cockpit development and automated testing. Additionally, the company’s Knowledge Management solution enhances productivity by streamlining access to technical information, and generative AI automates tasks like generating product data sheets from mechanical drawings.
AMZ201 | ML infrastructure at Zoox that powers autonomous driving of robotaxis
Zoox's mission is to make personal transportation safer, cleaner, and more enjoyable for everyone. Zoox aims to accomplish this by providing mobility-as-a-service in dense urban environments. Take, for example, its recently deployed and purpose-built robotaxi in Las Vegas. In this talk, learn how they built the ML Infrastructure that powers autonomous driving and other ML use cases. Hear context on how data is collected from robotaxis and how the company built their compute, training, and serving infrastructure leveraging various OSS tools and AWS services.
AIM120-S | Revolutionizing Audi's tender process with generative AI (sponsored by Capgemini)
TenderToucan, Audi’s AI tool, fundamentally changes Audi’s tender process using LLMs to compare offers against requirements. It reduces burdensome work for employees and leaves them with more time for analytical tasks. This results in highly accurate evaluations that take less time than before. This session covers user-centric development, continuous optimization, and mitigating AI replacement fears. Gain insights into balancing AI automation with human judgment and practical guidance for implementing AI solutions. TenderToucan showcases gen AI’s potential in transforming business processes, boosting efficiency, accuracy, and speed, setting new standards in tender management for the automotive industry and beyond. This presentation is brought to you by Capgemini, an AWS Partner.
AUT201 | Toyota drives innovation & enhances operational efficiency with gen AI
Toyota is in the midst of a transformative journey, harnessing the power of generative AI to drive innovation, boost productivity, and enhance operational efficiency. In this session, gain insights into Toyota's generative AI–driven initiatives that you can apply to own AI transformations. Discover how Toyota uses AI to capture and transfer critical institutional knowledge from retiring employees, reduce mean time to repair production line equipment, and decrease battery scrappage. Additionally, discover Toyota’s innovative approach to accelerating mainframe modernization using generative AI, reducing migration timelines by up to 50% while introducing new business capabilities.
AIM383-S | Toyota, Deloitte & AWS: Enhancing customer experiences & market share (sponsored by Deloitte)
Toyota Motor North America initiated a program with Deloitte that enhances customer and team member experiences, ultimately leading to a boost in market share and profitability. In this session, learn about the program, which focuses on improving the capabilities of their vehicle supply chain team through the implementation of AWS innovative technologies. Explore how these technologies enable frequent vehicle production ordering and scenario simulations, reducing the need for manual efforts and providing profit-optimized recommendations to drive vehicle sales. Finally, discover how the program facilitates the modernization of legacy applications, promoting efficient operations and delivering significant business value. This presentation is brought to you by Deloitte, an AWS Partner.
AUT307 | Transforming AV/ADAS development at Continental with generative AI
Autonomous vehicle (AV) and advanced driver-assistance systems (ADAS) development requires a data-driven process that relies on hundreds of petabytes of drive data and complex tool chains. Join this breakout session to learn how Continental and AWS are collaborating to accelerate the AV/ADAS development process in the cloud. This session outlines how AWS can help offload undifferentiated heavy lifting, such as streamlining data management and simplifying tool chain integration. It then introduces how generative AI accelerates the process of identifying and managing the 1–2% of relevant data within multi-modal datasets for model training, fine-tuning, and system validation.
BIZ219 | Transforming BMW sustainability operations with AWS and Catena-X
BMW, a renowned automotive manufacturer, is collaborating with AWS to lead the way in sustainable and transparent supply chain management practices within the automotive industry. This session explores the need for a comprehensive product carbon footprint (PCF) capability that encompasses supplier emissions data collection, augmentation, aggregation, validation, and audit to streamline the exchange of supplier certificates.
MAM208 | Transforming manufacturing with AWS, RISE with SAP, and Amazon
Leading manufacturers are using RISE with SAP, purpose-built AWS services, and Amazon’s extensive sourcing and logistics capabilities to transform their operations. In this session, hear how manufacturers have migrated to RISE with SAP on AWS, streamlining operations and benefiting from the performance, reliability, and security of ERP in the cloud. Learn how companies are extending their SAP environments to MES and PLM systems with 200+ AWS services—including generative AI, IoT, and analytics—to optimize productivity, quality, machine availability, and sustainability. Lastly, discover how Amazon Business and Supply Chain by Amazon can help optimize procurement, global shipping, storage, and fulfillment.
AIM117-S | Unlocking mission-critical new lines of business with AWS and gen AI (sponsored by Capgemini)
Join this inspiring session on the transformative journey of Penske Transportation Solutions. Discover how the innovative connected fleet program revolutionized fleet management. Learn how Penske used AWS ML/AI and generative AI services for predictive maintenance cost savings and automation efficiencies. Explore their strategic adoption of cloud technologies to introduce groundbreaking services, elevate customer satisfaction, and unlock new revenue streams. Gain insights into the business drivers and architectures processing terabytes of information at high speed. Don’t miss this chance to learn how AWS can drive your business growth and innovation. This presentation is brought to you by Capgemini, an AWS Partner.
SUS304 | Using AI/ML for sustained energy efficiency in industrial operations
Reducing energy consumption in operational and industrial sites is critical for organizations to stay on track with their sustainability goals. AI applications can make it radically easier for organizations to optimize their energy consumption. In this session, learn how machine learning (ML) can help derive new insights using historical data from equipment-based controllers with simulations and forecasting strategies for sustained energy efficiencies. Learn how Volkswagen Poznan and Amazon have implemented ML solutions to achieve energy optimizations across their operations and facilities.
Builders' session
WPS301-R1 | AI-driven traffic management for safer cities [REPEAT]
In this builders’ session, explore how AI and machine learning can revolutionize traffic management to enhance safety and reduce congestion in urban areas. Gain hands-on experience in deploying technologies to collect and analyze real-time traffic data, build predictive models, and optimize traffic flow dynamically. Create a simulated traffic environment, configure sensors, and establish a data pipeline. Build and train a machine learning model and then deploy it using serverless computing for real-time predictions. Ideal for developers, data scientists, and traffic management professionals, this session aims to create a functional AI-driven traffic management prototype. You must bring your laptop to participate.
WPS301-R | AI-driven traffic management for safer cities [REPEAT]
In this builders’ session, explore how AI and machine learning can revolutionize traffic management to enhance safety and reduce congestion in urban areas. Gain hands-on experience in deploying technologies to collect and analyze real-time traffic data, build predictive models, and optimize traffic flow dynamically. Create a simulated traffic environment, configure sensors, and establish a data pipeline. Build and train a machine learning model and then deploy it using serverless computing for real-time predictions. Ideal for developers, data scientists, and traffic management professionals, this session aims to create a functional AI-driven traffic management prototype. You must bring your laptop to participate.
AUT303 | AI-powered vehicle diagnostics and root cause identification
Join this hands-on session to build a generative AI–powered vehicle diagnostics and troubleshooting application. Use the Generative AI Application Builder (GAAB) on AWS with Amazon Bedrock Guardrails to analyze vehicle issues, diagnostic data (DTCs, CAN bus data), and sensor readings. Explore how to configure and deploy generative AI applications with Retrieval Augmented Generation (RAG) to query repair manuals and historical records, use vehicle symptoms or DTCs to generate root cause analyses and recommended repairs, and build a workflow using Amazon Bedrock Agents for multistep automotive diagnostic tasks. Also learn how to use prompt engineering to generate outcomes in different languages. You must bring your laptop to participate.
MFG304 | Build a unified namespace and connect factories at scale
This hands-on builders’ session guides you through the process of connecting Siemens PLCs at scale, determining the exposed data, and generating an AWS IoT SiteWise hierarchy using generative AI with Amazon Bedrock. Learn how to take exposed data from a brownfield PLC; create an ISA-95-compliant asset hierarchy using AWS IoT SiteWise, AWS IoT Greengrass, and Amazon Bedrock; and build a dashboard displaying live data. This session offers a step-by-step, practical approach to mastering the skills needed to build a unified namespace and connecting a factory at scale. You must bring your laptop to participate.
AUT304-R | Build a vehicle insights assistant with AWS IoT and Amazon Q [REPEAT]
In this interactive session, use AWS IoT to ingest vehicle data and then use Amazon Q to build a conversational generative AI–powered assistant that helps analyze the data using natural language queries and responses. Ask questions about the data like “Which vehicles have a low battery charge?” or “What are average vehicle speeds in the morning versus evening?” Learn how you can use Amazon Q to explore advanced querying and analysis capabilities like filtering, aggregations, and anomaly detection, and discover how Amazon Q can help you fine-tune your data collection campaigns or maintenance schedules based on collected data. You must bring your laptop to participate.
AUT304-R3 | Build a vehicle insights assistant with AWS IoT and Amazon Q [REPEAT]
In this interactive session, use AWS IoT to ingest vehicle data and then use Amazon Q to build a conversational generative AI–powered assistant that helps analyze the data using natural language queries and responses. Ask questions about the data like “Which vehicles have a low battery charge?” or “What are average vehicle speeds in the morning versus evening?” Learn how you can use Amazon Q to explore advanced querying and analysis capabilities like filtering, aggregations, and anomaly detection, and discover how Amazon Q can help you fine-tune your data collection campaigns or maintenance schedules based on collected data. You must bring your laptop to participate.
AUT304-R1 | Build a vehicle insights assistant with AWS IoT and Amazon Q [REPEAT]
In this interactive session, use AWS IoT to ingest vehicle data and then use Amazon Q to build a conversational generative AI–powered assistant that helps analyze the data using natural language queries and responses. Ask questions about the data like “Which vehicles have a low battery charge?” or “What are average vehicle speeds in the morning versus evening?” Learn how you can use Amazon Q to explore advanced querying and analysis capabilities like filtering, aggregations, and anomaly detection, and discover how Amazon Q can help you fine-tune your data collection campaigns or maintenance schedules based on collected data. You must bring your laptop to participate.
AUT304-R2 | Build a vehicle insights assistant with AWS IoT and Amazon Q [REPEAT]
In this interactive session, use AWS IoT to ingest vehicle data and then use Amazon Q to build a conversational generative AI–powered assistant that helps analyze the data using natural language queries and responses. Ask questions about the data like “Which vehicles have a low battery charge?” or “What are average vehicle speeds in the morning versus evening?” Learn how you can use Amazon Q to explore advanced querying and analysis capabilities like filtering, aggregations, and anomaly detection, and discover how Amazon Q can help you fine-tune your data collection campaigns or maintenance schedules based on collected data. You must bring your laptop to participate.
MFG303-R1 | Building a generative AI–powered shop floor assistant [REPEAT]
Learn how to build a generative AI assistant to analyze data from industrial IoT sensors, documents, manuals, and other manufacturing systems. Also learn how to provide natural language summaries of operation statuses and current issues with suggestion actions, and how to help operators, manufacturing engineers, and factory leaders conduct Q&A–based exploratory root cause analysis to increase overall plant productivity. You must bring your laptop to participate.
MFG303-R2 | Building a generative AI–powered shop floor assistant [REPEAT]
Learn how to build a generative AI assistant to analyze data from industrial IoT sensors, documents, manuals, and other manufacturing systems. Also learn how to provide natural language summaries of operation statuses and current issues with suggestion actions, and how to help operators, manufacturing engineers, and factory leaders conduct Q&A–based exploratory root cause analysis to increase overall plant productivity. You must bring your laptop to participate.
MFG303-R | Building a generative AI–powered shop floor assistant [REPEAT]
Learn how to build a generative AI assistant to analyze data from industrial IoT sensors, documents, manuals, and other manufacturing systems. Also learn how to provide natural language summaries of operation statuses and current issues with suggestion actions, and how to help operators, manufacturing engineers, and factory leaders conduct Q&A–based exploratory root cause analysis to increase overall plant productivity. You must bring your laptop to participate.
Chalk talk
MFG308-R1 | Build a seamless network between the factory shop floor and the cloud [REPEAT]
In the world of modern manufacturing, the concept of a ubiquitous network has emerged as a game-changer, promising to revolutionize the way we connect, process, and leverage data across production systems. Imagine an environment where computing and communication capabilities are seamlessly embedded into every aspect of your manufacturing operations, enabling real-time access to information and services, anytime and anywhere. This chalk talk explains how to build such a network on AWS and accelerate various manufacturing use cases such as predictive maintenance, quality control, supply chain optimization, and energy management, while addressing best practices and considerations for a successful implementation.
MFG308-R | Build a seamless network between the factory shop floor and the cloud [REPEAT]
In the world of modern manufacturing, the concept of a ubiquitous network has emerged as a game-changer, promising to revolutionize the way we connect, process, and leverage data across production systems. Imagine an environment where computing and communication capabilities are seamlessly embedded into every aspect of your manufacturing operations, enabling real-time access to information and services, anytime and anywhere. This chalk talk explains how to build such a network on AWS and accelerate various manufacturing use cases such as predictive maintenance, quality control, supply chain optimization, and energy management, while addressing best practices and considerations for a successful implementation.
ENU312 | Convergence of OT/IT data in the cloud: An energy industry use case
In this chalk talk, you learn how to build a secure global operational technology and information technology (OT/IT) network on AWS, connecting disparate and remote assets like solar farms or well sites to the cloud via OPC Unified Architecture servers, supervisory control and data acquisition systems, and programmable logic controllers. The architecture promotes a 100% private OT/IT network, segregates OT/IT traffic in transit and at rest, and implements the Purdue model on AWS.
AUT306-R | Customize small language models for automotive applications [REPEAT]
In this chalk-talk, attendees learn how to build and deploy domain-specific small language models (SLMs) for automotive use-cases. Explore how Amazon SageMaker can be used to fine-tune an SLM using industry terminology, and how the SLM can be scaled using Amazon Bedrock. Dive deeper with specific use-case examples, including code interrogation and generation on internal code base and Reinforcement Learning with Human Feedback (RLHF) for in-vehicle voice assistant applications. Attendees learn skills and techniques to create and deploy fine-tuned foundation models for the automotive industry.
AUT306-R1 | Customize small language models for automotive applications [REPEAT]
In this chalk-talk, attendees learn how to build and deploy domain-specific small language models (SLMs) for automotive use-cases. Explore how Amazon SageMaker can be used to fine-tune an SLM using industry terminology, and how the SLM can be scaled using Amazon Bedrock. Dive deeper with specific use-case examples, including code interrogation and generation on internal code base and Reinforcement Learning with Human Feedback (RLHF) for in-vehicle voice assistant applications. Attendees learn skills and techniques to create and deploy fine-tuned foundation models for the automotive industry.
MFG310 | Deploying an MES in the cloud or at the edge on AWS Outposts
Manufacturers today are looking at how the cloud can provide flexibility and resilience, as well as reduce cost for their production critical systems. Manufacturing execution system (MES) can be deployed in the cloud or for manufacturers who need low latency or have limited bandwidth on an AWS Outpost running at the edge. In this chalk talk, deep dive into the architectural patterns for deploying a MES system on AWS and on an AWS Outpost, including network topology and connectivity. This talk also walks through the reference architecture for running Siemens Opcenter Execution on AWS in general and on AWS Outposts in particular.
MFG301 | Design an industrial data foundation for generative AI in manufacturing
This chalk talk dives deep into the architectural patterns that underpin an industrial data strategy. This foundation is critical to enabling the application of generative AI for use cases such as assisted diagnosis and troubleshooting, advanced quality defect detection, and automated information modeling and digital threads. In addition to sharing and whiteboarding architectural patterns for operational and enterprise data ingestion, data storage and transformation, and contextualization, the talk showcases generative AI manufacturing use cases with live demos and code samples.
MKT308 | DevOps approach for software-defined everything with AWS Marketplace
To create software-defined everything (SDx) products, device manufacturers need to improve software collaboration and integration quality. This requires an agile and cloud-friendly approach compared to legacy on-premises development kits and restrictive software licenses. AWS Marketplace is helping AWS users create a cloud-based CI/CD pipeline and development environment with virtualized hardware. This chalk talk shows how AWS Marketplace is enabling the software-defined transformation for vehicles, medical devices, and manufacturers. See how users are able to scale the onboarding of their software vendors into their product development workflows and become modern software organizations.
MFG315 | Edge-to-cloud robotic solutions for optimizing manufacturing processes
Within manufacturing, the integration of robotics has revolutionized operations. However, successful implementations require careful planning. Robotic simulation is a powerful tool to virtually test and validate robotic systems before physical deployments, minimizing risks and optimizing processes. This chalk talk presents architectural patterns and a demonstration of robotic simulation with AWS IoT Greengrass and AWS IoT Core, enabling edge-to-cloud connectivity for manufacturers. This approach facilitates a validation of robotic systems using real-world data from Open 3D Engine (O3DE) simulators and AWS IoT Core, enabling manufacturers to simulate the entire manufacturing process including robotic systems, conveyors, and other equipment before physical implementation.
IOT318 | Efficient fleet operations and driver monitoring using AWS IoT and AI
Fleet operators need to effectively manage dashcam footage from their vehicles for various purposes, including law enforcement reporting, insurance, and driver training. In this interactive chalk talk, learn how to streamline access to relevant videos, reduce storage costs, and improve response times to agencies. Also explore how to use dashcam footage to train machine learning models that can provide real-time driver alerts for distracted driving situations. Leave this session with best practices and solutions for fleet operators that help reduce distracted driving, reduce costs, and improve overall operational efficiency while ensuring quick access to critical information when needed.
AUT310-R | End-to-end acceleration of vehicle software development [REPEAT]
The vehicle software development lifecycle is more than just writing lines of code. Months are spent in requirements engineering, code development and unit testing, and software validation. In this chalk talk, experts dive into each of these areas, showcasing how AWS can help accelerate the process with generative AI for interactive requirements development, code generation, and test-case generation. Learn how this, coupled with virtual validation targets on AWS, can enable up to 80% of the software development process to take place in the cloud, achieving a shift left in development and validation by somewhere between 6 and 18 months.
AUT310-R1 | End-to-end acceleration of vehicle software development [REPEAT]
The vehicle software development lifecycle is more than just writing lines of code. Months are spent in requirements engineering, code development and unit testing, and software validation. In this chalk talk, experts dive into each of these areas, showcasing how AWS can help accelerate the process with generative AI for interactive requirements development, code generation, and test-case generation. Learn how this, coupled with virtual validation targets on AWS, can enable up to 80% of the software development process to take place in the cloud, achieving a shift left in development and validation by somewhere between 6 and 18 months.
MFG311-R1 | Engineer and develop innovative products faster with generative AI [REPEAT]
In this session, learn how generative AI can be used in product engineering and development, from responding to a Request for Proposal (RFP) to generating new concepts and developing digital threads. Watch how to extract the key functional, technical, compliance, and user experience requirements from multiple document types including 2D technical drawings. Explore how to share data across engineering disciplines in various languages and how to enrich generative design for new product ideas. This session showcases some of these generative AI product engineering use cases with live demos and code samples.
MFG311-R | Engineer and develop innovative products faster with generative AI [REPEAT]
In this session, learn how generative AI can be used in product engineering and development, from responding to a Request for Proposal (RFP) to generating new concepts and developing digital threads. Watch how to extract the key functional, technical, compliance, and user experience requirements from multiple document types including 2D technical drawings. Explore how to share data across engineering disciplines in various languages and how to enrich generative design for new product ideas. This session showcases some of these generative AI product engineering use cases with live demos and code samples.
MFG312 | Managing value-chain product carbon emissions data with generative AI
Manufacturers face increasing demand from customers and public authorities to accurately model, calculate, and report on their product-based carbon emissions. A credible assessment requires internal data management capabilities and the efficient exchange of high-trust information with suppliers. For larger manufacturers this may involve scaling to thousands of suppliers and/or products. Learn how connectivity, trust, and information exchange come together in the value chain, and about the mechanisms behind the modeling and calculation of product-based carbon emissions — and how it all can be accelerated using generative AI services on AWS.
IOT319 | Modernize your connected vehicle platform with new AWS IoT features
A connected vehicle platform is critical for delivering innovative features like remote start from a mobile app, electric vehicle battery range estimation, and video streaming for enhanced vehicle security. Join this chalk talk to learn about the newest capabilities from AWS IoT FleetWise, AWS IoT Core, and Amazon Kinesis Video Streams that can help you modernize your connected vehicle platforms and drive innovation. Walk through how to build for key use cases using features and methods that optimize for secure connectivity, low latency, cost efficiency.
IOT311-R | Seamless migration: Safely transitioning large IoT fleets to AWS [REPEAT]
In an era where managing extensive fleets of IoT devices and backend systems poses significant challenges, transitioning to managed solutions like AWS IoT Core becomes imperative. In this chalk talk, dive into the intricate process of migrating vast numbers of devices and backend services from self-managed brokers to AWS IoT, enabling a controlled and risk-free transition. Learn essential techniques to seamlessly migrate to AWS IoT Core without perceptible impact, minimizing error surfaces and enabling quick rollbacks in case of failures. Leave this talk with expert-level guidance on how to safely and efficiently migrate to the cloud, empowering your IoT infrastructure for the future.
IOT311-R1 | Seamless migration: Safely transitioning large IoT fleets to AWS [REPEAT]
In an era where managing extensive fleets of IoT devices and backend systems poses significant challenges, transitioning to managed solutions like AWS IoT Core becomes imperative. In this chalk talk, dive into the intricate process of migrating vast numbers of devices and backend services from self-managed brokers to AWS IoT, enabling a controlled and risk-free transition. Learn essential techniques to seamlessly migrate to AWS IoT Core without perceptible impact, minimizing error surfaces and enabling quick rollbacks in case of failures. Leave this talk with expert-level guidance on how to safely and efficiently migrate to the cloud, empowering your IoT infrastructure for the future.
AUT309 | Securing generative AI in automotive: The Security Scoping Matrix
As generative AI ignites innovation across a wide array of automotive use cases, it is essential to prioritize security. This chalk talk reviews the Generative AI Security Scoping Matrix, which is designed to provide a mental model for the five types of generative AI solution patterns in automotive and the unique security considerations for specific example applications. Then, learn how to apply the scoping matrix to an automotive generative AI use case, leveraging best practices for securing the example application using AWS services and techniques that support responsible generative AI adoption.
MFG313 | Transforming manufacturing operations: AWS e-bike smart factory demo
In this session, dive deep into how manufacturers can leverage AWS services and partner solutions to optimize their manufacturing operations. This chalk talk uses the story of a fictitious e-bike company and a purpose-built e-bike smart factory demo. Through an architectural walk through, explore the use of AWS industrial IoT, generative AI, AI/ML, and analytics services that were used to build the demo for the use case. This includes real-time visibility of production metrics, detection of equipment anomalies, automated quality inspection and defect detection, and a generative AI assistant that provides contextual insights and guided troubleshooting.
MFG309 | Use generative AI to transform product R&D docs into MBSE models
In this chalk talk, learn how generative AI can transform product R&D documentation into actionable model-based systems engineering (MBSE) models. Organizations developing highly complex, safety-critical products like aircraft, space systems, and medical equipment require extensive collaboration across engineering disciplines and global stakeholders. Traditionally, this has relied on using documents for R&D specification and design. Explore how users can leverage generative AI to migrate from document-based to model-based systems engineering approach to help reduce design cycle times and improve operational readiness.
MFG314 | Using autonomous robot & gen AI technologies for an industrial facility
Autonomous robot inspection solutions have the potential to mitigate unplanned downtime due to undetected issues caused by human errors or knowledge gaps. They can also reduce work-related injuries inside hazardous plant environments, improve cost-efficiency, and increase productivity through the fully automated inspection process. In this chalk talk, discover the collaborative journey of Air Products, ANYbotics, and AWS on building and deploying the inspection solution in one of Air Products’ facilities, as well as using gen AI technologies to analyze and provide insights to the inspection results. Explore learnings, challenges, and best practices for creating value from this technology.
Workshop
MFG306 | A connected & optimized supply chain with AWS Supply Chain & gen AI
Supply chain-related processes and solutions usually rely on complex environments made by homegrown applications, several siloed execution systems, and point-to-point integrations. This can lead into a lack of visibility and consequent inefficiency in making the right decisions at the right time. AWS Supply Chain is able to mitigate risks, lower costs, improve visibility, and accelerate the decision-making process thanks to ML- and LLM-powered connectors, ML-powered insights and recommendations, generative AI–powered insights and analysis. In this workshop, learn how to set up the application, ingest the data, generate a demand forecast and supply plan, and use generative AI fine-tuned for supply chain to extract insights. You must bring your laptop to participate.
AUT305 | Accelerate software development with Amazon Bedrock and Amazon Q
Join this workshop to learn how to increase developer efficiency and streamline software-defined vehicle development using generative AI features within the Virtual Engineering Workbench. First, walk through how app developers use the Virtual Engineering Workbench to code, validate, and innovate on an Android Automotive app, using virtual electronic control units (ECUs). Next, explore how to adjust a virtual ECU within a few minutes and publish it as part of the Virtual Engineering Workbench for potentially thousands of users. Generative AI will help us reduce the publishing time to a minimum. You must bring your laptop to participate.
MFG305 | Building a smart factory with Amazon Q Business
Learn how to build and deploy an AI assistant that seamlessly integrates with AWS services, enabling interaction with your industrial data in real time. Imagine an assistant that can answer questions like “What is the OEE for this line?” or compose maintenance requests. This workshop walks through the process of deploying an API to interface with industrial IoT services and creating a custom plugin in Amazon Q Business. Coding experience isn’t required, but some API design and industrial automation knowledge is helpful. Leave this workshop with a functional AI assistant that can be tailored to your factory’s needs. You must bring your laptop to participate.
IOT314 | Generative AI recommendations for effective alarm management
In this hands-on workshop, learn how to reduce operator response times with a generative AI–powered alarm management system and managed alarm events. Traditionally, when an operator receives a critical alarm due to equipment malfunction or process deviation, they must gather information from various sources including event details, sensor data, manuals, and standard operating procedures that are often scattered across data silos. This workshop demonstrates how you can build an effective alarm management system using AWS services like AWS IoT SiteWise, AWS IoT Events, Amazon Bedrock, and Amazon SNS to notify operators with contextual event information and a repair plan, enhancing the operator performance. You must bring your laptop to participate.
AUT302 | Multi-container AV/ADAS simulations with Autoware and AWS Batch
It can be complex, time-consuming, and error-prone to run autonomous vehicle and advanced driver assistance system (AV/ADAS) simulations using a single container due to the diversity of simulation components (simulation environment, test scenarios, software under test). In this hands-on workshop, learn how to use AWS Batch to run your AV/ADAS simulations as logical independent containers, in parallel, at scale. Build a CARLA simulation in an Amazon ECS/Amazon EC2 compute environment using separate containers for the simulation and autonomy stacks. Run multiple scenarios, upload the results to Amazon S3, and view them in a dashboard. You must bring your laptop to participate.
MFG307 | Use ML for CAE simulation to morph geometries and predict flow fields
Jump into the role of a simulation engineer who is redesigning a vehicle’s exterior and has to show critical metrics to leadership. Learn how to deploy the AWS machine learning (ML) for simulation toolkit, and prepare a generative AI–enabled engineering environment to see how fast simulation can be. You can upload your own vehicle geometry or choose one that’s provided for you, morph it using generative AI, get aerodynamic flow field and KPI predictions, and experience how to exceed leadership expectations by delivering engineering data days ahead of schedule. Get hands-on with advanced product engineering techniques. You must bring your laptop to participate.
IOT317 | Video-based driver monitoring with AWS IoT and AI/ML
Learn how to build an IoT device for edge computer vision and machine learning (CVML) workloads, with a focus on detecting driver fatigue and distraction. Deploy your CVML model to the edge to detect driver events in real time, and use generative AI in the cloud to retrospectively search video content at scale using natural language. Get step-by-step instructions on how to implement the solution using AWS IoT Greengrass, Amazon Kinesis Video Streams, AWS IoT Core, and Amazon Bedrock. You must bring your laptop to participate.